{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ece599aa",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pygame 2.5.2 (SDL 2.28.2, Python 3.7.5)\n",
      "Hello from the pygame community. https://www.pygame.org/contribute.html\n"
     ]
    }
   ],
   "source": [
    "import cartpole\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "9bdebc4d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-0.04584679,  0.00908167, -0.01438346, -0.04326243])"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "env = cartpole.CartPoleEnv()\n",
    "env.reset()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "70f5e075",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f8f6a7144d0>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "env.step(1)\n",
    "plt.imshow(env.render())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "c440fa76",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.01037579, -0.02159264,  0.03598075,  0.00210069])"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "env.reset()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d0ec465e",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
